Joonho Lee

Auxiliary-field quantum Monte Carlo (AFQMC) is a systematically improvable many-body method, but its application to extended solids has been severely limited by unfavorable computational scaling and memory requirements that obstruct rigorous access to the thermodynamic and complete-basis-set limits. By combining tensor hypercontraction with k -point symmetry, we reduce the computational and memory scaling of AFQMC for solids to O ( N 3 ) and O ( N 2 ) , respectively, with an arbitrary basis, comparable to diffusion Monte Carlo. This enables simultaneous, controlled extrapolation of full-system AFQMC calculations to the thermodynamic and complete-basis-set limits across insulating, metallic, and strongly correlated solids, without embedding, local approximations, empirical finite-size corrections, or composite schemes. Our results establish AFQMC as a general-purpose, systematically improvable alternative to diffusion Monte Carlo and coupled-cluster methods for predictive simulations of solids, enabling accurate energies and magnetic observables within a unified framework.

The electrochemical activity of PtGa arises from Ga corrosion that enriches surface Pt sites, instead of previously claimed topological surface states.

In many cases, the predictions of machine learning interatomic potentials (MLIPs) can be interpreted as a sum of body-ordered contributions, which is explicit when the model is directly built on neighbor density correlation descriptors and is implicit when the model captures the correlations through the non-linear functions of low body-order terms. In both cases, the “effective body-orderedness” of MLIPs remains largely unexplained: how do the models decompose the total energy into body-ordered contributions, and how does their body-orderedness affect the accuracy and learning behavior? In answering these questions, we first discuss the complexities in imposing the many-body expansion on ab initio calculations at the atomic limit. Next, we train a curated set of MLIPs on datasets of hydrogen clusters and reveal the inherent tendency of the ML models to deduce their own, effective body-order trends, which are dependent on the model type and dataset makeup. Finally, we present different trends in the convergence of the body-orders and generalizability of the models, providing useful insights into the development of future MLIPs.

We present an efficient algorithm for constructing an all-electron periodic Coulomb matrix based on Ewald summation combined with the Fourier-transformed Coulomb method. The short-range contributions involving compact densities are evaluated in real space using standard Gaussian density fitting. For the long-range contributions, we introduce an integral-direct plane wave density fitting scheme that is applicable to both compact and diffuse densities. The resulting method achieves orders-of-magnitude speedups for prototypical solid-state systems compared to a closely related approach, the range-separated density fitting method. Using the dispersion-corrected PBE functional with all-electron Dunning and Karlsruhe basis sets, we apply our method to compute the cohesive energy of the benzene crystal and the adsorption energy of CO on the MgO(001) surface. These results are in good agreement with existing literature. Our approach enables efficient Gaussian-based semi-local density functional calculations using dense k-point meshes and traditional molecular Gaussian basis sets.

Matthias Degroote, Joonho Lee and Pauline Ollitrault introduce the Digital Discovery themed collection on “Quantum computing for chemistry, material science and biotechnology”.

Second-order Møller-Plesset perturbation theory (MP2) for ab initio simulations of solids is often limited by divergence or overcorrelation issues, particularly in metallic, narrow-gap, and dispersion-stabilized systems. We develop and assess three regularized second-order perturbation theories: κ-MP2, σ-MP2, and the size-consistent Brillouin-Wigner approach (BW-s2) across metals, semiconductors, molecular crystals, and rare gas solids. BW-s2 achieves high accuracy for cohesive energies, lattice constants, and bulk moduli in metals, semiconductors, and molecular crystals, rivaling or surpassing coupled-cluster with singles and doubles at a lower cost. In rare gas solids, where MP2 already underbinds, κ-MP2 does not make the results much worse, while BW-s2 struggles. These results illustrate both the potential and limitations of regularized perturbation theory for efficient and accurate solid-state simulations. While broader testing is warranted, BW-s2(α = 2) appears particularly promising, with possible advantages over modern random-phase approximations and coupled-cluster theory.

We present a numerical method for grand canonical density functional theory (DFT) tailored to solid-state systems, employing Gaussian-type orbitals as the primary basis. Our approach directly minimizes the grand canonical free energy using the density matrix as the sole variational parameter, while self-consistently updating the electron number between self-consistent field iterations. To enable realistic electrochemical modeling, we integrate this approach with implicit solvation models. Our solvation scheme introduces less than 50% overhead relative to gas-phase calculations. Compared to existing plane wave-based implementations, our method shows improved robustness in grand canonical simulations. We validate the approach by modeling corrosion at silver surfaces, finding excellent agreement with previous studies. Our method is implemented in the quantum chemistry software Q-Chem. This work lays the groundwork for future wave function-based simulations beyond DFT under electrochemical operando conditions.

The transfer tensor method (TTM) [Cerrillo and Cao, Phys. Rev. Lett. 112, 110401 (2014)] can be considered a discrete-time formulation of the Nakajima–Zwanzig quantum master equation (NZ-QME) for modeling non-Markovian quantum dynamics. A recent paper [Makri, J. Chem. Theory Comput. 21, 5037 (2025)] raised concerns regarding the consistency of the TTM discretization, particularly a spurious term at the initial time t = 0. This work presents a detailed analysis of the discretization structure of the TTM, clarifying the origin of the initial-time correction and establishing a consistent relationship between the TTM discrete-time memory kernel KN and the continuous-time NZ-QME kernel K(NΔt). This relationship is validated numerically using the spin-boson model, demonstrating convergence of reconstructed memory kernels and accurate dynamical evolution as Δt → 0. While the TTM provides a consistent discretization, we note that alternative schemes are also viable, such as the midpoint derivative/midpoint integral scheme proposed in Makri’s work. The relative performance of various schemes for either computing accurate K(NΔt) from exact dynamics or obtaining accurate dynamics from exact K(NΔt) warrants further investigation.

We present an efficient algorithm for the all-electron periodic Coulomb matrix based on the Ewald summation combined with the Fourier-transformed Coulomb method. The short-range contributions involving compact densities are evaluated in real space using the standard Gaussian density fitting method. For the long-range contributions, we introduce an integral-direct planewave density fitting, applicable to both compact and diffuse densities. The resulting method achieves orders-of-magnitude speedups for prototypical solid-state systems compared to a closely related approach, the range-separated density fitting method. Using dispersion-corrected PBE functional and all-electron Dunning and Karlsruhe basis sets, we apply our method to compute the cohesive energy of the benzene crystal and the adsorption energy of CO on the MgO(001) surface. These results are in good agreement with existing literature. Our approach enables efficient Gaussian-based semi-local density functional calculations using dense $\mathbf {k}$-point meshes and traditional molecular Gaussian basis sets.